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import gradio as gr
# Backend processing function
def process_text(input_text):
# Example processing: Return the text with a prefix
return f"Processed Text: {input_text}"
# Define the Gradio interface
with gr.Blocks() as demo:
# Title
gr.Markdown("# Speech-to-Text Demo with Web Speech API")
# Input and output elements
with gr.Row():
input_box = gr.Textbox(label="Speech-to-Text Input", elem_id="speech-input")
output_box = gr.Textbox(label="Processed Output")
with gr.Row():
speech_button = gr.Button("Start Speech Recognition", elem_id="speech-button")
# Link the input box to the backend processing function
speech_button.click(process_text, inputs=input_box, outputs=output_box)
# Inject JavaScript for Web Speech API
gr.HTML("""
<script>
// Function to initialize and start the Web Speech API
function startSpeechRecognition() {
const recognition = new (window.SpeechRecognition || window.webkitSpeechRecognition)();
recognition.lang = 'en-US'; // Set language
recognition.interimResults = true; // Enable real-time updates
recognition.continuous = true; // Keep listening for multiple sentences
// Handle results
recognition.onresult = function(event) {
const transcript = Array.from(event.results)
.map(result => result[0].transcript)
.join('');
document.getElementById("speech-input").value = transcript; // Update the input box
};
// Handle errors
recognition.onerror = function(event) {
console.error("Speech Recognition Error:", event.error);
alert("Speech recognition error: " + event.error);
};
recognition.start(); // Start listening
}
// Attach the start function to the button click
document.getElementById('speech-button').addEventListener('click', startSpeechRecognition);
</script>
""")
# Launch the demo
demo.launch(share=True, port= 20005) |